source("global.R")
display_x <- panimmune_data$sample_selection_choices[1]
display_y <- panimmune_data$cell_content_choices[1]
internal_x <- get_variable_internal_name(display_x)
internal_y <- get_variable_internal_name(display_y)
plot_df <- panimmune_data$df %>%
select_(.dots = c(internal_x, internal_y)) %>%
.[complete.cases(.),]
plot <- create_violinplot(
plot_df,
internal_x,
internal_y,
internal_x,
xlab = display_x,
ylab = display_y,
fill_colors = decide_plot_colors(panimmune_data, internal_x)
)
the condition has length > 1 and only the first element will be used
plot

ggplotly(plot) %>%
layout(hovermode = "closest")
plot_df %>%
plot_ly(
x = ~Subtype_Immune_Model_Based,
y = ~leukocyte_fraction,
split = ~Subtype_Immune_Model_Based,
type = 'violin',
box = list(
visible = T
),
meanline = list(
visible = T
)
)
let(
alias = c(
xvar = "leukocyte_fraction",
yvar = "Dendritic_cells.Aggregate2"
),
plot_df %>%
plot_ly(
x = ~xvar,
y = ~yvar
) %>%
layout(
title = "C6",
xaxis = "Leukocyte Fraction",
yaxis = "Macrophages"
)
)
No trace type specified:
Based on info supplied, a 'scatter' trace seems appropriate.
Read more about this trace type -> https://plot.ly/r/reference/#scatter
No scatter mode specifed:
Setting the mode to markers
Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
Error: $ operator is invalid for atomic vectors
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